One-click deployment
Pick an open-source LLM and deploy it with a single click — the model, the serving stack, and the GPU environment are provisioned automatically.
LLM as a Service
One-click deployment · dedicated GPU environment
Your own LLM, deployed in one click.
Deploy any open-source LLM on a scalable GPU environment that belongs to you alone — and get a production API endpoint for your applications. It is a system dedicated to you: fully isolated and protected, never shared with other tenants.
Overview
A private LLM system, deployed in one click
LLM as a Service gives your organization its own open-source LLM deployment. Choose your model and your GPU capacity, and a production-ready API is provisioned on infrastructure reserved for you alone.
Scalable GPU environment
Choose a fixed number of GPUs, or let capacity auto-scale up and down as your workloads change.
A production API endpoint
Every deployment issues an API endpoint built for production traffic — ready for your applications from day one.
Yours alone
The environment is single-tenant and completely isolated. Your system is shared with nobody — not at the hardware, not at the model layer.
How it works
From choice to production API in four steps
No DevOps, no GPU procurement, no model-serving engineering. The platform handles the infrastructure; your team handles the application.
Choose your model
Select any open-source LLM from the catalog — or bring your own.
Set your capacity
Define a fixed number of GPUs, or enable auto-scaling to match demand.
Deploy with one click
The environment, model, and serving stack are provisioned for you alone.
Connect your applications
A production API endpoint is issued — your team integrates and ships.
Your system, in Japan
Isolated by design. Data protection through domestic deployment.
Your model runs on GPU capacity deployed in data centers across Japan — on an environment that belongs to your organization alone.
Full data residency in Japan
Inference runs on GPU capacity deployed across data centers in Japan. Your prompts and completions stay in-country.
Private endpoint
Your API is served through a private endpoint — reachable from your own network, never through shared infrastructure.
Shared with nobody
Single-tenant isolation at every layer. No other customer can see your model, your data, or your traffic.
Billing & control
Per GPU-second, with limits you set
You are charged for the GPU capacity your deployment actually uses, metered per GPU-second — with spending and usage limits that you control.
Per-GPU-second billing
Pay only for the GPU capacity your deployment consumes, metered per GPU-second. No idle premiums, no surprise invoices.
Limits you set
Define your own spending and usage limits. Your deployment operates within the boundaries you choose.
Full spend visibility
Real-time usage and spend tracking in the financing dashboard, with downloadable invoices for finance.
Enterprise features
Built for regulated workloads
The controls your security and compliance teams require — designed in from the start.
VPC peering and private endpoints
Connect from your own network without traversing the public internet.
Audit logging
A detailed audit trail of model usage and access, exportable for your compliance team.
Usage analytics
Per-team and per-application usage views for internal chargeback and oversight.
Contractual availability
High-availability SLAs guaranteed in writing, with a dedicated onboarding team.
Who it's for
For organizations that need their own LLM
LLM as a Service is designed for organizations that handle sensitive data and want a private generative-AI foundation under their own control.
Document processing
Contracts, applications, and correspondence — extracted and summarized on your own system, in-country.
Internal copilots
Answer engines over internal knowledge, with access control and auditability your compliance team can review.
Customer service AI
Assisted and automated responses that keep customer data inside your own boundary.
Your model. Your data. Your environment. Your control.
Deploy your own LLM
Tell us about your model requirements, expected workloads, and compliance constraints. We will respond within one business day with next steps and a technical walkthrough.